[PDF] Top 20 A study of attention based neural machine translation model on Indian languages

... Neural machine translation (NMT) models have recently been shown to be very successful in machine translation ...in machine translation has significantly improved the ... See full document

... The attention mechanism evaluates the dis- tribution of to-be-translated source words in a content-based addressing fashion (Graves et ...to attention faults and generate fluent but inaccurate or ... See full document

... of neural ma- chine translation models, the invention of the Transformer model is one of the most important ...RNN- based neural machine translation ...learning ... See full document

... original attention weight is sometimes hard to ...two languages, en-ko NMTs tend to generate diverse sentences and they have very different orderings among each ... See full document

... roughly based on oversim- plified matching algorithms at word-level, whose resulting products provide limit- ed extension associated with user input- ...the attention- based neural ... See full document

... the attention mechanism provides NMT models with a boost in performance, it also significantly increases the computational bur- ...the attention model has to compute the alignment weights for all the ... See full document

... MSD model for phrasal reordering; Xiong et ...feature-rich model to learn phrase reordering for BTG; and Li et ...a neural network method to learn a BTG reordering ...some neural network ... See full document

... improving attention models (Luong et ...local attention models to improve translation ...the attention-based NMT to include structural biases from word-based alignment models, ... See full document

... Neural machine translation (NMT) has gained a lot of attention recently due to its substantial im- provements in machine translation quality achiev- ing state-of-the-art ... See full document

... GEC model generally aims to robustly correct grammatical errors in any writ- ten text partly because the task difficulty varies depending on proficiency levels and essay top- ...a model outperforms a ... See full document

... highest attention score to the unknown ...sub-word- based vocabulary by the BPE method. The vocabulary based on the sub-words can cover much more words in German and Russian, compared to the ... See full document

... state-of-the-art attention-based NMT, by using images as words in the source sen- tence, to initialise the encoder’s hidden state and as additional data in the initialisation of the de- coder’s hidden ... See full document

... We proposed augmenting transformer models with an alignment head to help extract alignments in scenarios such as dictionary-guided transla- tion. We demonstrated that the alignment- assisted systems can achieve ... See full document

... Neural machine translation (Cho et al., 2014) (NMT) systems based on sequence-to-sequence models (Sutskever et ...use attention mechanisms (Bahdanau et ...the model can produce ... See full document

... tures based on attention weights of a neural machine translation system and cross-lingual phrase embeddings as input features of a re- gression ...a neural machine ... See full document

... new attention mecha- nism that explicitly takes the attention history into consideration when generating the attention ...tention based NMT, the next word to attend is highly dependent on the ... See full document

... Recently, neural machine translation (NMT) based on neural networks (NNs) is known to provide both high-precision and human-like translation through its simple ...encoder-decoder ... See full document

... using attention scores in the ANMT models can be an alternative to using alignment tools (Jean et ...in translation tasks where characters and words are shared across different ...results based on ... See full document

... German translation, we achieve new state-of-the-art (SOTA) results for both WMT’14 and WMT’15, outperforming previous SOTA systems, backed by NMT mod- els and n-gram LM rerankers, by more than ...and ... See full document

... the translation history and then integrates it into the attention ...the attention history and Sankaran et ...attention model. In addition, Zhang et al. (2017) improve the ... See full document